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Multi-GNSS Precise Point Positioning (MGPPP)

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: closed (20 January 2025) | Viewed by 6174

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Special Issue Editors

Dr. Bingbing Duan

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Guest Editor

Institute for Astronomical and Physical Geodesy, Technical University of Munich, Arcisstr 21, 80333 Munich, Germany
Interests: GNSS orbit modeling; precise GNSS orbit determination; GNSS signal biases; PPP-AR; LEO satellite orbit determination, and the combination of space techniques (GNSS, DORIS, SLR, VLBI)
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Prof. Dr. Urs Hugentobler

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Guest Editor

Institute for Astronomical and Physical Geodesy, Technical University of Munich, Arcisstr 21, 80333 Munich, Germany
Interests: precise applications of GNSS such as positioning, precise orbit determination, reference frame realization, time transfer, and other space techniques, such as DORIS, SLR, and VLBI

Dr. Jiang Guo

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Guest Editor

Royal Observatory of Belgium,3 Avenue Circulaire, B1180 Brussels, Belgium
Interests: high-precision GNSS positioning; real-time satellite clock and multi-frequency phase bias determination; multi-GNSS and multi-frequency ambiguity resolution; GNSS time transfer

Special Issue Information

Dear Colleagues,

Precise Point Positioning (PPP) is a technique that allows users to achieve centimetre- and millimetre-level positioning accuracy based on a single GNSS receiver. This is of central importance for many applications (i.e., plate tectonics, surface loading, earthquake monitoring) and also has a massive uptick in interest across multiple industries (i.e., surveying, precise agriculture, autonomous vehicles/drones, low-cost and dual-frequency chipsets for the mass-market, smartphone). Currently, PPP is typically combined with ambiguity resolution or RTK (Real Time Kinematic) technique and evolved to PPP-AR and PPP-RTK. To support this, Galileo and BDS satellite systems start the provisioning of HAS (high-accuracy service) and PPP-B2b service, respectively.

Multi-GNSS, multi-frequency, and multi-signal adopt more measurements and enable more new options in the linear combination than using the legacy dual-frequency measurements in PPP. On the other hand, this also makes it more challenging to handle different types of biases in ambiguity resolution. This Special Issue aims to discuss advances in using Multi-GNSS, multi-frequency, and multi-signal in PPP/PPP-AR/PPP-RTK, as well as in the computation of atmospheric parameters. New updates and assessments of HAS, PPP-B2b, or other services in smartphone, ground station, and low-earth orbit (LEO) satellite positioning are welcome, too.

Dr. Bingbing Duan
Prof. Dr. Urs Hugentobler
Dr. Jiang Guo
Guest Editors

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Keywords

multi-GNSS
multi-frequency
multi-signal
PPP-AR
PPP-RTK
high-accuracy service
real-time PPP-AR

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Published Papers (5 papers)

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Research

18 pages, 1898 KiB

Open AccessArticle

Improving Performance of Uncombined PPP-AR Model with Ambiguity Constraints

by Yichen Liu, Urs Hugentobler and Bingbing Duan

Remote Sens. 2024, 16(23), 4537; https://doi.org/10.3390/rs16234537 - 3 Dec 2024

Viewed by 1075

Abstract

With the advancement of multi-frequency and multi-constellation GNSS signals and the introduction of observable-specific bias (OSB) products, the uncombined precise point positioning (PPP) model has grown more prevalent. However, this model faces challenges due to the large number of estimated parameters, resulting in strong correlations between state parameters, such as clock errors, ionospheric delays, and hardware biases. This can slow down the convergence time and impede ambiguity resolution. We propose two methods to improve the triple-frequency uncombined PPP-AR model by integrating ambiguity constraints. The first approach makes use of the resolved ambiguities from dual-frequency ionosphere-free combined PPP-AR processing and incorporates them as constraints into triple-frequency uncombined PPP-AR processing. While this approach requires the implementation of two filters, increasing computational demands and thereby limiting its feasibility for real-time applications, it effectively reduces parameter correlations and facilitates ambiguity resolution in post-processing. The second approach incorporates fixed extra-wide-lane (EWL) and wide-lane (WL) ambiguities directly, allowing for rapid convergence, and is well suited for real-time processing. Results show that, compared to the uncombined PPP-AR model, integrating N1 and N2 constraints reduces averaged convergence time from 8.2 to 6.4 min horizontally and 13.9 to 10.7 min vertically in the float solution. On the other hand, integrating EWL and WL ambiguity constraints reduces the horizontal convergence to 5.9 min in the float solution and to 4.6 min for horizontal and 9.7 min for vertical convergence in the fixed solution. Both methods significantly enhance the ambiguity resolution in the uncombined triple-frequency PPP model, increasing the validated fixing rate from approximately 80% to 89%. Full article

(This article belongs to the Special Issue Multi-GNSS Precise Point Positioning (MGPPP))

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19 pages, 8896 KiB

Open AccessArticle

Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations

by Mohammed Abou Galala and Wu Chen

Remote Sens. 2024, 16(23), 4463; https://doi.org/10.3390/rs16234463 - 28 Nov 2024

Viewed by 572

Abstract

Signal distortion bias (SDB) in Global Navigation Satellite System (GNSS) data processing, defined as the time difference between the distorted chip and the ideal rectangular chip, leads to systematic biases in pseudoranges, affecting satellite and receiver differential code biases (DCBs). The stability of SDBs, allowing them to be treated as constant values, highlights the importance of investigating both their stability and estimation accuracy. Two different methods are used to estimate SDBs: (1) the hybrid method and (2) the geometry-free method. Data from approximately 430 stations, spanning the entire year of 2021, were analyzed to evaluate the estimation accuracy and the short-term and long-term stability of GPS SDBs. The analysis focused on two code signals: C1C (L1 Coarse/Acquisition) and C2W (L2 P(Y)). The results show that the short-term and long-term stability of GPS C1C and C2W SDBs is comparable for both methods, with only minor variations between them. Additionally, one month of data were used to validate the accuracy of estimated SDBs across different receiver groups. The results demonstrate that geometry-free SDBs provide stable satellite DCB estimates with an average bias below 0.15 ns and minimal residual biases, while hybrid SDBs provide satellite DCB estimates with an average bias below 0.20 ns. Overall, the comparison underscores the superior performance of geometry-free SDBs in achieving consistent satellite DCB estimates. Full article

(This article belongs to the Special Issue Multi-GNSS Precise Point Positioning (MGPPP))

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17 pages, 6683 KiB

Open AccessArticle

Affordable Real-Time PPP—Combining Low-Cost GNSS Receivers with Galileo HAS Corrections in Static, Pseudo-Kinematic, and UAV Experiments

by Grzegorz Marut, Tomasz Hadas, Kamil Kazmierski and Jaroslaw Bosy

Remote Sens. 2024, 16(21), 4008; https://doi.org/10.3390/rs16214008 - 28 Oct 2024

Cited by 1 | Viewed by 1644

Abstract

The Galileo High Accuracy Service (HAS) is a free of charge Global Navigation Satellite System (GNSS) augmentation service provided by the European Union. It is designed to enable real-time Precise Point Positioning (PPP) with a target accuracy (at the 95% confidence level) of 20 cm and 40 cm in the horizontal and vertical components, respectively, to be achieved within 300 s. The performance of the service has been confirmed with geodetic-grade receivers. However, mass market applications require low-cost GNSS receivers connected to low-cost antennae. This paper focuses on the performance of the real-time static and kinematic positioning achieved with Galileo HAS and low-cost GNSS receivers. The study is limited to GPS + Galileo dual-frequency positioning, thus exploiting the full potential of Galileo HAS SL1. We demonstrate that the target accuracy of Galileo HAS SL1 is reached with both geodetic-grade and low-cost receivers in dual-frequency static and kinematic applications in open-sky conditions. Precision of a few centimeters is reached for static positioning, while kinematic positioning results in subdecimeter precision. Vertical accuracy is limited by missing phase center offset models for low-cost antennas. In general, the performance of low-cost hardware using Galileo HAS for real-time PPP is comparable to that of geodetic-grade hardware. Therefore, combining low-cost GNSS receivers with Galileo HAS is feasible and justified. Full article

(This article belongs to the Special Issue Multi-GNSS Precise Point Positioning (MGPPP))

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22 pages, 6884 KiB

Open AccessArticle

Carrier Phase Common-View Single-Differenced Time Transfer via BDS Penta-Frequency Signals

by Wei Xu, Wenbin Shen, Lei Liang, Chao Yan, Pengfei Zhang, Lei Wang and Jia Song

Remote Sens. 2024, 16(21), 3955; https://doi.org/10.3390/rs16213955 - 23 Oct 2024

Viewed by 1078

Abstract

The BeiDou Navigation Satellite System (BDS-3) has officially provided services worldwide since July 2020. BDS-3 has added new signals for B1C, B2a and B2b based on old BDS-2 B1I and B3I signals, which brings opportunities for achieving high-precision time transfer. In this research, the BDS-3/BDS-2 combined penta-frequency common-view (CV) single-differenced (SD) precise time transfer model is established with B1I, B3I, B2I, B1C, B2a and B2b signals, including dual-, triple-, quad- and penta-frequency (abbreviated as DF, TF, QF and PF) ionosphere-free (IF) combination CV SD models. Taking four long baseline time links (from 637.6 km to 1331.6 km) as examples, the accuracy and frequency stability of the BDS-3/BDS-2 combined DF, TF, QF and PF SD time transfer models were evaluated. The experimental results show that the frequency stability of the TF, QF and PF SD models were improved by 2.5%, 5.3% and 8.5%, on average, over the DF SD model. Compared with the traditional DF (B1I/B3I IF combination) SD model, the standard deviation (STD) of the multi-frequency SD model was reduced by 5.9%, on average, and the frequency stability was improved by 4.0% on average, which had the most apparent effect on the improvement of short-term frequency stability. Specifically, the DF1 (B1C and B2a DF IF combination), TF1 (B1C, B2a and B2b TF IF combination), QF1 (B1C, B1I, B2a and B2b QF IF combination) and PF4 (B1C, B1I, B2a, B2b and B3I PF IF combination) SD models had better performance in timing, and the PF4 SD model had the best performance. Considering that the PF4 (one PF signal IF combination) SD model does not require an estimated inter-frequency bias and that its noise factor is minor compared with the PF1 (four DF signal IF combination), PF2 (three TF signal IF combination) and PF3 (two QF signal IF combination) SD models, we recommend the PF4 SD model for multi-frequency time transfer and the use of the PF2, PF2 or PF3 SD model to supplement the PF4 SD model in cases of penta-frequency observation loss. Full article

(This article belongs to the Special Issue Multi-GNSS Precise Point Positioning (MGPPP))

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17 pages, 4629 KiB

Open AccessArticle

A Method for Constructing an Empirical Model of Short-Term Offshore Ocean Tide Loading Displacement Based on PPP

by Hai Wang, Xingyuan Yan, Meng Yang, Wei Feng and Min Zhong

Remote Sens. 2024, 16(16), 2998; https://doi.org/10.3390/rs16162998 - 15 Aug 2024

Viewed by 972

Abstract

The ocean tide loading (OTL) can result in displacements of centimeters or even decimeters at nearshore stations. Global ocean tide models exhibit errors in nearshore regions, which limit the accuracy of maintaining the coordinates of these stations. GNSS positioning can obtain tidal load displacements in nearshore areas, but it often requires long-term observation data and cannot provide timely correction models for newly established reference stations. This paper proposes a method for an empirical correction model of short-term OTL displacements using GNSS observations, where the kinematic coordinate sequences are first obtained by multi-GNSS precise point positioning with ambiguity resolution (PPP-AR), and then the OTL corrections are obtained by window-sliding forecast based on random forest modeling. Through experiments conducted in the Hong Kong region, the empirical model with a window of 15 days is established by the proposed method. After applying the empirical model, root mean square errors of the residuals are reduced by 1.5 (30.6%), 3.7 (53.6%), and 3.7 mm (37.8%) in the East, North, and Up (ENU) components, respectively. When using the global ocean tide model FES2014, the RMSE values are reduced by 1.2 (24.5%), 0.3 (4.3%), and 3.7 mm (37.8%) in the ENU components, respectively. The empirical model shows better effects for the OTL displacement compared to FES2014, especially in the N component, with an improvement ratio of about 49.3%. Full article

(This article belongs to the Special Issue Multi-GNSS Precise Point Positioning (MGPPP))

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